Nice job by the umpire, BUT: a better throw from Marsh would have had the runner at the plate. It's a shame the throw was offline. Hard to find fault with Marsh since he's been hitting so well, but a better throw would have kept the streak alive (and can you imagine the drama?).
A thing I’ll always love about baseball, check out the ump towards the end of the video just making up a random mess on home plate he has to “clean” to let the fans/ Sanchez enjoy the moment. Always appreciated stuff like that a lot.
And I’m very excited to see what you and your team do with the next generation of this! So happy you’re bringing the idea back into the mainstream that has been dominated by the LLM juggernaut. (And happy to be of any assistance if I can be of any help.)
The basic idea of world models is very old.
Optimal control folks were using model-based planning in the 1960s (using the "adjoint state" methods, which deep learning people would now call "backprop through time").
But the real question is what you do with this idea and how you reduce it to practice.
Congrats, @ylecun!! Well done.
Of course many of us AI researchers have been working on world models since the 1970's, so let's make sure all of that great historical work doesn't get forgotten or reinvented...
📢 BREAKING: FT reports that Yann LeCun’s startups AMI Labs raises $1.03 bn to build world models, at a pre-money valuation of $3.5bn.
Congratulations @ylecun 🚀
The financing positions the company as a test of LeCun's belief that today's large language models fall short of human-level reasoning and autonomy.
LeCun earlier said AMI aims to build systems capable of reasoning and planning in complex real-world settings.
AMI Labs (Advanced Machine Intelligence Labs) aims to solve the limitations of standard language models by building world models using the Joint Embedding Predictive Architecture to observe spatial data.
This visual framework helps the AI internalize how objects behave so it can safely plan complex actions.
Relying exclusively on text limits AI to human linguistic output while ignoring the massive bandwidth of unspoken physical laws.
Building predictive spatial architectures is the mandatory leap required to achieve reliable autonomous agents.
Building predictive spatial architectures is the mandatory leap required to achieve reliable autonomous agents.
This fundraising included backing from a global group of investors, including France’s Cathay Innovation, Amazon founder Jeff Bezos’s Bezos Expeditions, Singapore’s Temasek, Seoul-based SBVA and US chip giant Nvidia.
The company's near-term target customers are organizations operating complex systems, including manufacturers, automakers, aerospace companies, biomedical firms and pharmaceutical groups.
Over time, he added, the technology could also support consumer applications. "What consumers could be interacting with is a domestic robot. You need a domestic robot to have some level of common sense to really understand the physical world."
LeCun said he was also talking with Meta about potentially deploying the technology in its Ray-Ban Meta smart glasses. "That's probably one of the shorter term potential applications," he said.
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ft .com/content/e5245ec3-1a58-4eff-ab58-480b6259aaf1
How did machine learning get to this amazingly successful point? My new podcast tells the story of the field with the help of a dozen major contributors such as @geoffreyhinton , @ylecun , @RichardSSutton , @tdietterich and others. https://t.co/Djq0SiwSeg
BREAKING: Yann LeCun has raised a HUGE $1.03bn round for his new startup, in Europe's largest seed EVER!
It values Advanced Machine Intelligence (AMI) at a WHOPPING $3.5bn!
The company, based in Paris, is aiming to develop the next generation of AI models that go beyond LLMs.
It is aiming to build world models that learn abstract representations of reality, similar to the mental models humans use to reason and guide action in the physical world.
These systems predict how situations evolve, and how actions lead to consequences, so that they can plan sequences of actions under real-world constraints.
It has just announced raising $1.03bn at a $3.5bn valuation co-led by Hiro Capital, Cathay Innovation, Greycroft, HV Capital, and Jeff Bezos Expeditions.
In February it was revealed that UK-based Ineffable Intelligence was raising a $1bn seed. Now French AMI is raising a $1.03bn seed.
Both of these companies are aiming to take AI beyond LLMs, and if they succeed, could build some of the most important technology in the world.
European Tech is COOKING and we love to see it
🚨 Don't miss this amazing opportunity!
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📅 Deadline: Aug 15, 2025
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@PHLEaglesNation This sure was a prescient pre-season take. And neither the defense nor the head coach turned out to be as suspect as Stephen A. suggested they would be.
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🚨Looking for a job in immunology and biotech research? IMPRINT is #hiring! Join us to help revolutionize how we decode the body’s immune memory, uncover the causes of chronic diseases, and drive breakthroughs in autoimmunity and neuropsychiatric research.
IMPRINT is seeking passionate individuals for the following roles:
🔹Experimental Director (NYC)
🔹Scientist, Molecular Biology & Immunology (NYC)
🔹Computational Immunologist / Machine Learning Scientist / Biostatistician (ideally based in Germany, but open to outstanding candidates across the EU, Canada, and the US)
✨ Full role descriptions here: https://t.co/HH9EKCIoXY
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May 7 - Computing Research Association-Industry Blockchain in Industry Virtual Roundtable - should be a great event. Please join us!:
https://t.co/iYOYAZ4Fjf